海洋沉积硅藻研究方法与应用综述
王艳娜1,2, 刘东艳2,*
1.中国科学院大学,北京 100049
2.中国科学院海岸带环境过程与生态修复重点实验室(烟台海岸带研究所),山东烟台 264003
刘东艳(1973-),女,山东青岛人,研究员,主要从事海洋藻类生态学研究. E-mail:dyliu@yic.ac.cn

王艳娜(1983-),女,山东德州人,博士研究生,主要从事海洋沉积硅藻研究. E-mail:ynwang@yic.ac.cn

摘要

针对海洋沉积硅藻的研究方法及其应用,分别从沉积硅藻的纯化方法、数据分析及其环境学应用3个方面进行了概述。纯化方法主要分为4个步骤:去除碳酸钙、去除有机质、去除矿物质和制片,依次介绍了各步骤中常用的处理方法和方法改进,分析比较了其各自的优缺点。在数据分析方面,为确保数据的可靠性,从硅藻种类鉴定与计数、数据表达、误差评价3个方面,详述了所需的方法原则,以便最大程度地消减误差。在此基础上,进一步解释了如何运用数值分析方法来提高分析的精准度。国际上,对沉积硅藻在反演环境演变方面的应用已经开展了较深入的研究,包括表层沉积硅藻与上层水环境的关系,利用深层沉积硅藻重建古海洋环境、追踪盐度梯度以及反演水体富营养化等。针对国内该研究的不足,倡导今后应综合多学科的技术手段,结合上层水体观测资料,以推进我国沉积硅藻定量化的研究并增强反演环境的准确性。

关键词: 海洋沉积硅藻; 硅藻分离纯化; 数值方法; 海洋环境学应用
Review of the Analysis and Application of Diatoms in the Marine Sediments
Wang Yanna1,2, Liu Dongyan2
1.University of Chinese Academy of Sciences,Beijing 100049, China
2.Key Laboratory of CoastalEnvironmental Processes and Ecological Remediation, Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, Yantai 264003, China
Abstract

With regard to the analysis and application of diatoms in the marine sediments, diatom purification method, data analysis method and diatom application in environmental reconstruction were summarized. The diatom purification is composed of four main processes (removing calcium carbonate, organic and minerogenic matter, and slide preparation). For each process, frequently used methods and improvements were introduced, while their pros and cons were compared. As to the data analysis, in order to ensure statistical reliability, the essential methods and principles were represented in detail with species identification and counting, data expression and error estimation involved to reduce errors as much as possible. On this basis, the numerical method application was explained for its advantage of improving the accuracy for analysis. The applications of diatom fossils in environmental reconstruction were studied more deeply abroad, including the investigation of relationship between diatom fossils and upperwater environment, the application of diatoms from deeper core sediment for reconstructing oceanic paleoenvironment, tracing salinity and reflecting eutrophication. As far as the deficiency of the domestic research was concerned, multidisciplinary technologies and observational data were suggested to be combined into the study in order to promote the quantitative research of diatom fossils and the accuracy of environmental reconstruction.

Keyword: Marine sedimentary diatom; Diatom extraction and purification; Numerical method; Paleo-oceanographic application.
1 引言

硅藻是海洋生态系统中重要的初级生产者[ 1],其物种数量及群落结构变化会直接影响到海域的初级生产力、生物地球化学过程乃至温室气体浓度[ 2, 3],并间接影响海洋渔获量[ 4]。硅藻对环境变化反应敏感,其物种组成、数量变化和地理分布依赖各种物化条件,故蕴含丰富的生态与环境信息,成为公认的指示生物[ 5, 6]。硅藻的细胞壁抗溶性强,能在沉积物中长期保存,其形态、大小、花纹又可作为物种鉴定依据,因此,20世纪初,研究者已将其作为指示生物并广泛应用于古海洋学研究中[ 7 9]。本文综述了近年来国内、外海洋沉积硅藻研究中的纯化和分析方法的改进及环境应用的进展,旨在为国内学者提供该领域研究动态。

2 硅藻纯化方法

沉积硅藻的纯化方法是通过一系列实验室手段处理样品,去除沉积物中的其他组分,将硅藻从沉积物中提取出来的方法,大致分为物理和化学两大类方法。焚烧法是常见的物理方法,即直接取不含矿物质的新鲜湿样置于载玻片上,加热至灰白后,粘合制片(图1)。此法可快速去除有机质,且能较完整的保留硅壳[ 10],但焚化后的硅壳脆弱易碎,不宜制作永久玻片[ 11];化学法的流程比较复杂,主要包括4个步骤(图1):去除碳酸钙等无机物,去除有机质,去除矿物杂质及提取硅藻制片。具体操作及改进如下:

2.1 去除碳酸钙等

根据样品量、样品含钙量情况,加入适量稀盐酸(5~15%),通常静置12 h使之充分反应[ 12]。盐酸的作用不仅可以除碳酸钙,同时帮助去除金属盐与金属氧化物[ 10]。这一过程还有助于分离聚集于粘土中的硅藻,大部分硅壳能够解析并沉降下来,利于之后的制片过程[ 12, 13]

2.2 去除有机质

强酸法和过氧化氢法是去除有机质的主要方法[ 7, 10]。Van der Werff[ 14]最早选用强酸去除有机质,即依次加入足量的浓硫酸、重铬酸钾(至饱和)及草酸,至溶液澄清;Simonsen只加入高锰酸钾和盐酸;von Stosch则用浓硝酸和浓硫酸共同反应[ 15]。而后者的方法中还可用重铬酸钾催化提效[ 16]。强酸法去除有机质效率高,且反应平静,不会翻腾溢出损失样品。然而,反应过程中残留的钙质化合物会形成难以去除的石膏晶体[ 10],影响后期制片;且重铬酸钾反应后还会释放有毒铬物质,故多不推荐使用[ 7]

Battarbee[ 17]首次使用30%的过氧化氢并加热来去除有机质,减少了额外杂质的产生。然而,对于有机质含量过高的样品,可引起剧烈反应,导致样品溢出[ 7]。改进的方法是不加热或降低过氧化氢浓度[ 7, 10],避免剧烈反应。只要添加硝酸溶液就能同时确保去除质量和效率[ 18]

2.3 去除矿物杂质,分离硅藻

上述2步反应后,仍存留的沙砾、黏土等杂质可用物理手段去除。包括:纯水冲洗样品,待硅藻沉降后(3~5h),移除上层浊液,多次重复可彻底去除悬浮的黏土[ 7, 10, 12]。为防止硅藻丢失,可用显微镜检查弃液中是否有硅藻损失,以选定恰当的沉降时间[ 10];此过程中可加入增强黏土悬浮性的试剂,如焦磷酸钠、氨水、稀释的织物柔软剂、加尔贡硬水软化剂(含磷酸钠和碳酸钠)等,静置一晚,以充分分散黏土[ 1, 7, 10, 19]。此外,过筛法也可帮助去除粗颗粒(≥0.5mm)[ 10]

硅藻的分离通常利用重液浮选法,原理是根据硅藻与矿物质的比重不同而将2者分离。Battarbee[ 10]详述了从配制重液到清洗硅藻的浮选步骤,且推荐使用聚钨酸钠配制重液。Rings等[ 20]引入微池分流重力场流分离技术(Split-flow lateral-transport thin, SPLITT),利用重力控制分离硅藻。该方法具有高产低耗,无需试剂的优点,但设备昂贵,尚难以推广。

2.4 制片

纯化后的硅藻经定容、均匀后,可定量制成永久性玻片。针对硅藻在玻片上分布不均匀的问题,Battarbee[ 21]设计了蒸发盘技术,使硅藻均匀沉降于盘底的盖玻片上,得到均匀且便于统计的制片。统计部分硅藻就可较精确地推算出硅藻浓度、种类比例,大大节省了鉴定的时间;但蒸发过程耗时长、易受扰动,并未被广泛应用。

图1 海洋沉积硅藻的纯化步骤Fig.1 Flow diagram for marine sedimentarydiatoms’purification and slides preparation

3 数据分析方法

数据分析方法是针对不同的研究目的,运用各种分析手段,对获取的硅藻种类、数量数据进行多方面分析,提取信息的方法。

3.1 统计数据获取

3.1.1 种类鉴定与计数

长期以来,硅藻鉴定几乎完全依赖鉴定人员的分类鉴定水平,且耗时、耗力。近年来,计算机自动识别系统(如ADIAC项目)快速发展[ 22],虽然只是在其中某些小类群(科、属级)中探索尝试,远未达到全面应用的成熟程度,但还是有效地辅助了硅藻分类。先进的计算机鉴定技术还引入形态标准化。如傅里叶分析方法中,沿硅壳轮廓取若干点,用傅里叶级数分解拟合形状,建立周期函数以描述轮廓曲线[ 23, 24];再如形态测量技术中,用点距离、矢量等手段将硅藻生理特征点数字化,通过数学运算区别结构的细微变化。此法尤其利于鉴别形态相似的种类[ 25]

获得硅藻物种及统计数量的过程中,仍需注意以下问题:(1)残损硅壳的计数原则。多于一半的硅壳记为1个;中心纲物种可见中央区的残片记为1个;羽纹纲物种可用中心区或端部计数;休眠孢子可单独计数[ 1, 10, 17]。(2)硅藻的统计数量在300~600个,种类比例已无明显变化,符合统计要求[ 10]。同时,可利用Serieyssol等[ 7]建立的累计丰富度曲线判断必要计数量,曲线达到水平恒定时表明计数符合统计要求(图2)。

图2 硅藻计数的累计丰富度曲线[ 7]4条曲线分别代表来自法国4个地区的样品;绿线Marais表明计数到250即可Fig.2 Relationships between the numbers of valves counted and diatom species recorded (Accumulative richness curves)[ 7]The 4 curves stand for the samples collected in 4 regions in France, respectively; The green curve (Marais) shows that the count of only 250 was satisfying

3.1.2 数据表达

硅藻的总数量通常为绝对丰度,计算公式为,

绝对丰度=样品中硅藻壳数(个)/样品干重(g)或体积(cm3)

群落结构的分析数据通常用各物种的相对丰度表示,即,

相对丰度=某种数量/硅藻总量×100%

各样品含有的硅藻种类繁多,样品间的硅藻种类、数量不尽相同。需删除无统计意义的稀有种(相对丰度极小);而有些相对丰度很大的优势种,则可能掩盖其它种类的变化趋势,需将数据进行对数转换[ 26]

在古生产力研究中,硅藻丰度变化可体现硅藻生产力情况。需要用“年龄—深度模型”估算出沉积物的累积率,即沉积物单位时间内的堆积净厚度(cm/a)[ 27],再计算“硅藻数量(壳数/cm3)×沉积物累积率(cm/a)”,硅藻生产力即表示为硅藻累积速率(壳数/cm2·a)[ 28]。当硅藻物种间细胞差异很大的时候,硅藻累积速率不能很好地反映其生产力,还需将硅藻累积速率再转换为硅藻生物量累积速率,即估算硅壳平均体积,将各种类的硅壳数量转换为生物体积以获取硅藻总体积,硅藻生物量累积速率则表示为μm3/cm2·a形式[ 10]

3.1.3 误差评价

较大的误差可导致错误结论,因此,数据的可靠性和误差评价十分重要。数据误差可能来自计数过程,如:硅质化较弱、直径较小或磨损的硅壳,给鉴定、计数增加困难;鉴定人员对硅壳残片计数习惯各异,也会导致误差。因此,确立统一的鉴定、计数原则很重要[ 5, 29]

建立误差评价方法也很重要。以Mosimann的统计理论为基础,结合运算软件(如MOSLIMIT,CONCENTR),可以定量计数与置信区间的关系来判定计数误差,即硅藻计数每增大4倍,种类百分比的置信区间变窄一倍,不可靠性随之降低[ 29, 30]。Maher等[ 29]设定置信限度(0.95、0.99、0.9995),以数据是否落入该置信区间来评价数据(硅藻浓度、种类之比等)的可靠性。评价硅藻或生物量累积速率的误差相对复杂,需将沉积物测年值的误差和硅壳体积估算的误差结合进去[ 29, 31]。如条件允许,还可经多次、多人、多实验室比较统计结果来消减上述误差[ 5, 29]

3.2 有效数据释读

深入释读硅藻数据,提取准确信息,有助于定量反演环境参数。John等[ 28]从数据概况、数据分析与数据释读三方面详述了这一过程(表1)。

表1 数据概况、数据分析和数据释读的相关数值方法[ 28] Table 1 List of relevant numerical methods for DS, DA, DI in relation to the assumed diatom species response model to the environmental variable(s) of interest[ 28]

数据概况:初步判断数据整体趋势(如硅藻组合的时空变化特征),比较不同样品与区域间的硅藻组合的异同。预分析获得有效数据、“典型值”(如均值、中位数)、差量(如方差、标准差)以及偏度、峰度来总结数据[ 32, 33],并利用图形方式(如直方图、散点图)揭示数据整体的结构、趋势和细节[ 34]。同时,通过聚类、分区和排序等统计方法,硅藻—环境变量的相关性分析,揭示硅藻数据的梯度,识别边界或“离群”样品,易于对影响因子建立假设并进行解释[ 35]

数据分析:评价数据的数值特征,包括硅藻组合内或多个组合的物种丰富度、时空变化趋势、沉积组合中的变化频率及硅藻—环境关系。评价物种对环境变量的最适值和耐受限度,比较不同种类在不同地区、环境的生态位,进而建立转换函数来定量反演环境特征及变化,分析环境的影响作用[ 28]

数据释读:通过检验假设,评价导致硅藻组合变化的“胁迫因素”,并根据影响大小,筛选关键的环境解释变量。硅藻古生态学中主要有2种检验假设方法:直接法和间接法。前者用环境数据直接检验假设的硅藻—环境关系是否成立;后者检验假设的硅藻—环境关系不成立的可能性,反推真实的关系[ 36]

4 沉积硅藻的环境应用
4.1 表层沉积硅藻—环境关系

建立沉积硅藻—环境关系的前提:特定的硅藻组合在特定环境下产生并保存。表层沉积硅藻是硅藻群落经海流迁移、沉降—再悬浮—埋藏后的结果[ 37]。在这一过程中,其携带的环境、气候信号已发生了改变,但大量观测结果证实其空间分布特征对上层海洋环境仍具指示作用,如:上升流系统、北极、赤道大西洋等海区[ 38 40]。然而,需谨记沉积硅藻组合空间分布特征仅反映海域环境在某段时期的平均状况,而不是环境现状[ 37]

表层沉积硅藻物种丰度与生物量的空间变化趋势,可以与海域的营养盐、海表温盐、海流变化建立关系[ 37]。如:在有上升流影响的海域,冷水性且营养盐需求高的物种通常分布在高营养、低温的上升流区域,而暖水性且营养盐需求低的物种则反之。再如:南大洋沉积物中一些种类的丰度在南北向的升/降趋势是适应不同温度范围的结果;北欧海区沉积硅藻的东西向变化范围则指示了东起大西洋暖流,西至海冰区的上层海域温度变化[ 41, 42]

建立目标海域的指示物种十分重要,指示物种的丰度变化可以帮助定量化反演海洋环境。如:南大洋沉积中的海冰种 Fragilariopsiscurta的相对丰度达70%时,指示-1~1⁰C的海表温度及8~11个月/年的海冰覆盖[ 43]。指示种的丰度变化趋势还能反映环境因子的变化方向,如: Fragilariopsiskerguelensis的丰度急降至0表明海表温度低于其最适温度后逐渐降低;而如果其丰度缓慢降低,则指示海表温度超过其最适温度并逐渐升高[ 44]

4.2 深层沉积硅藻—环境关系

深层沉积硅藻与现生组合一致时,可推知古海洋环境、气候条件可能与现代海洋类似[ 37]。根据沉积记录的分辨率,可分为低分辨率和高分辨率研究。早期的低分辨率研究通过分析硅藻群落的组成,并基于少数种类的现代生态表征,包括基于单一种类变化和种类间比例关系的变化(如:不同种类比、同种的不同变种比、同种的不同形态比、残片与完整壳体的比例)重建大尺度的古海洋环境[ 44 47]。如:用 Thalassiosiraantarctica随水温变化呈现的冷、暖形态定性反演全新世海表温度的变化[ 48, 49];用 Fragilariopsiscylindrus F. curta之比反演南大洋海冰覆盖程度[ 50]。然而,依靠少数指示种类或者单一指标提取的有限环境信息,会引起较大的反演误差。

高分辨率研究主要依靠分析亚毫米尺度的沉积物记录(如硅藻软泥),得到年际、年代际的硅藻数据,并引入扫描电镜[ 51],亚毫米分样[ 52],海面卫星遥感[ 53]等技术,充分挖掘其在环境反演中的潜力。比较而言,这种结合高精度硅藻数据与其它多参数(地化参数、遥感信息、现代水体的长周期观测数据)综合反演环境的方法可以显著减小研究误差;而基于硅藻—环境参数建立的转换函数,在一定程度上实现了反演海洋环境理化参数的半定量化研究。目前使用的各类转换函数虽基于不同数学原理,但都始于3个数据库,含3个步骤(图3)[ 37]

图3 转换函数重建环境3步简图[ 37]Fig.3 Schematic protocol of a transfer function highlighting the databases and the three-step mathematical technique[ 37]

这一点可以从利用硅藻组合对古盐度的追踪上得到启发。早期广泛用“halobion系统”,将研究水域的硅藻,按其生活的盐度范围,划分成5个以上盐度级的种类组合[ 54]。用组合—盐度关系可指示沉积物来源,亦可反演近岸地区古盐度,推知海平面升降、海岸线变迁等古海洋事件[ 55]。但此分类往往依据研究者对硅藻适盐性的经验,且常用同组硅藻种类划分不同盐度界线的“halobion系统”[ 56],这种不统一的划分很难准确定量古盐度。

最近20多年,研究应用回归模型计算各种类对盐度的最适值和耐受极限,含各种类盐度范围的标准集能定量重建盐度。标准集不仅完整展现了种类分布随盐度梯度的连续变化,且均一化处理环境参数可获得完整的盐度范围和准确的最适值,这在多因素干扰的自然态中很难得到。因此盐度标准集比“halobion系统”更适于定量反演盐度[ 57]

近年来,对海水富营养化的反演也体现了这些高精度的研究特征。海洋富营养化是初级生产者的有机碳生产率持续增长的过程,当达到301~500 g C/m2·a时则认为水体呈现富营养化[ 58]。通常人类活动使大量N、P入海是导致海洋富营养化的主要原因,且已严重威胁河口、近岸的水环境健康[ 59]。Anderson等[ 60]提出,引入沉积硅藻方法获取近海区域的营养盐背景值,有助于评价其现代水域的富营养化状况。即,用加权平均化的营养盐参数与表层沉积硅藻结合评价各物种在营养盐梯度上的分布范围和最适值,以此可以定量化反演营养盐参数;Clark等[ 61]和Weckström等[ 62]则结合多个地化指标(如溶解氧、总溶解氮、铵盐、(亚)硝酸盐、磷酸盐、(亚)硝酸盐:磷酸盐、叶绿素a等),并通过建立硅藻—营养盐转换函数分别综合反演了丹麦海区150年的总氮(TN)和芬兰海区的总溶解氮(TDN)变化,指出了富营养的演变过程。

5 国内研究进展及展望

我国海洋沉积硅藻的研究发展很快,已在广泛调查海洋表层、深层沉积硅藻种类、数量的基础上,应用沉积硅藻组合反演海洋环境的演变特征。如:王开发等针对东海陆缘第四纪沉积,调查分析了硅藻群落的种类、数量,探讨了古环境的演变[ 63 65];蓝东兆等学者,分析了南海、福建沿海及台湾海峡晚第四纪沉积硅藻,以此推断这些海区的地理环境变迁,追踪冲绳海槽的黑潮变化[ 66 68];蒋辉等不仅分析了我国南海的表层硅藻组合分布与海洋环境的关系[ 69, 70],还用WA-PLS方法重建了冰岛近海晚全新世的夏季海表温,详述了定量古环境气候的方法[ 71],诠释了建立现代沉积硅藻—环境变量数据库的先决性[ 72]。沉积硅藻—营养盐的转换函数法在我国湖泊总磷的研究中已较成熟[ 73],也可为海洋沉积硅藻定量营养盐的研究提供参考。

然而,我国在高分辨率的研究上与国际仍有差距。目前,由于学科之间的交叉程度不够,利用多参数综合判定古环境变化的研究较少。如:硅藻生物标志物、同位素参数的研究发展极快,但却往往与传统的分类研究处于分离状态,导致物种层面的优势难以结合进去。其次,与上层水体观测结果的结合研究不够。尽管我国缺乏长周期海洋观测数据,但建国以来已有的观测数据与十年际的遥感反演数据可以应用到古海洋学研究中,至少可以佐证一些现代过程的变化。因此,提出倡导在传统物种分类的水平上,综合多学科的技术手段(如生物标志物),推进硅藻的定量化研究;并能够结合上层水体观测资料,验证现代过程,增强反演的准确性。

The authors have declared that no competing interests exist.

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